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HER1/EGFR Inhibitor-Associated Rash: Future Directions for Management and Investigation Outcomes from the HER1/EGFR Inhibitor Rash Management Forum

2005· review· en· W2151979638 on OpenAlexaff
Román Pérez-Soler, Jean Pierre Delord, Allan C. Halpern, Karen Kelly, James G. Krueger, B. Massuti Sureda, Joachim von Pawel, Jennifer S. Temel, Salvatore Siena, Denis Soulières, Leonard B. Saltz

Bibliographic record

VenueThe Oncologist · 2005
Typereview
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsHôpital Notre-Dame
FundersNational Cancer InstituteGenentechF. Hoffmann-La Roche
KeywordsRashMedicineDermatologyAcneEGFR inhibitorsAdverse effectEtiologyEpidermal growth factor receptorPathologyInternal medicineCancer

Abstract

fetched live from OpenAlex

Abstract Learning Objectives After completing this course, the reader will be able to: Describe the clinical and pathological characteristics of the cutaneous rash secondary to anti-EGFR therapy.Explain the prognostic implications of the cutaneous rash secondary to anti-EGFR therapy.Discuss the treatment of the cutaneous rash secondary to anti-EGFR therapy. Access and take the CME test online and receive 1 hour of AMA PRA category 1 credit at CME.TheOncologist.com Skin rash associated with HER1/epidermal growth factor receptor (EGFR) inhibitors is common. The lack of clinical and patient guidance for this often chronic and sometimes distressing side effect makes rash management and etiology investigation high priorities. To address this, oncologists and dermatologists with experience with HER1/EGFR inhibitors attended the HER1/EGFR Inhibitor Rash Management Forum. Recommendations include continued analysis of the correlation between rash and clinical outcome and improving the accuracy and reproducibility of terminology and grading systems. Because acne vulgaris has a unique pathology, and the pathology and etiology of rash are unclear yet distinct from acne vulgaris, using such terms as acne, acne-like, or acneiform should be avoided. Until there is a specific dermatological definition, rash is best described using phenotypic terms for its appearance and location. It is currently unknown which agents are best for treating rash. Clinical trials of rash treatments are urgently required, and suggestions for agents to consider are made based on current knowledge. The effect of dose reduction or interruption on rash should also be investigated. Secondarily infected rash may be more frequent than has been previously recognized, and some investigators favor empiric use of an oral antibiotic if this appears to be the case. Suggestions for patients include makeup to camouflage the rash and an emollient to prevent and alleviate skin dryness. The increasing use of HER1/EGFR-targeted agents makes managing rash important. We hope the outcomes from this Forum provide background for future studies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.037
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0040.006
Open science0.0010.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0360.006

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.068
GPT teacher head0.369
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations275
Published2005
Admission routes1
Has abstractyes

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